It was not till November 2021 that GPT-3 had a public release. In fact, DALL.E 2’s predecessor DALL.E is yet to be publicly released.
DALL·E 2 is preferred over DALL·E 1 for its caption matching and photorealism when evaluators were asked to compare 1,000 image generations from each model.
Both of them have found wide usage in the field of image, video and voice generation, leading to a debate on what produces better results—diffusion models or GANs.
OpenAI said that it had achieved a new state-of-the-art (41.2 per cent vs 29.3 per cent) on the miniF2F benchmark.
The theorem prover achieved 41.2% vs 29.3% on the miniF2F benchmark, a challenging collection of high-school olympiad problems.
Compared to GPT-3, InstructGPT produces fewer imitative falsehoods (according to TruthfulQA) and are less toxic (according to RealToxicityPrompts).
OpenAI has introduced embeddings, a new endpoint in the OpenAI API, to assist in semantic search, clustering, topic modeling, and classification. OpenAI’s embeddings outperform top models in three standard benchmarks, including a 20% relative improvement in code search. Embeddings are really useful for working with natural language and code. The embeddings that are numerically similar […]
These seemingly similar models can be confusing to understand to decide which one will be the right choice to apply for a particular setting.
A look at a few of the interesting algorithms from OpenAI in 2021
With the battle between large text-to-image generation models heating up, let’s see what GLIDE and GauGAN2 bring to the table
GLIDE (Guided Language to Image Diffusion for Generation and Editing) is a 3.5 billion parameter text-to-image generation model
Latitude has unveiled the closed beta version of the platform Voyage to further expand into AI-powered games.